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    Deep learning tutorials

    Deep learning tutorials (2nd ed.)

    Week1

    1. Deep learning intro.
    2. Python basics
    3. Let's play with images & MNIST
    4. Terminologies

    Week2 - Do you know deep learning?

    1. CNN and AlexNet
    2. TensorFlow basics
    3. Logistic regression
    4. GoogLeNet
    5. AlphaGo: MCTS+CNN
    6. Let's implement MLP!
    7. Let's play with you OWN DATASET
    8. Regularization methods
    9. Optimization methods
    10. Restricted Boltzmann Machine
    11. Let's implement denoising autoencoder

    Week3 - CNN basics

    1. Semantic segmentation: FCN, DeconvNet, DeepLab with atrous conv
    2. Let's implement a simple CNN
    3. Let's implement a basic CNN
    4. Let's implement semantic segmentation
    5. Weakly supervised localization: Global average pooling
    6. Implement MLP and CNN on your OWN DATASET
    7. Denoising deconvolutional neural network

    Week4 - CNN applications + RNN basics

    1. Image detection (RCNN, SPPnet, FastRCNN, FasterRCNN)
    2. Other detections (YOLO, AttentionNet)
    3. Let's use TensorBoards
    4. RNN from Colah's blog
    5. Visual QnA: DPPnet + MCBP!
    6. Super resolution
    7. Deep reinforcement learning

    Week5 - RNN applications

    1. RNN basic + handwriting generation
    2. Let's implement RNNs
    3. Let's implement Word2vec
    4. Image captioning: Show and Tell + Show, attend and tell
    5. char-rnn + how can we use Hangul?

    Week6 - Deep learning is so FUN!

    1. Residual network and some analysis
    2. Neural Style: Texture synsthesis+Inverting CNN
    3. Let's implement neural style
    4. Bayesian optimization
    5. Adversaral attack?
    6. Generative adversarial network

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    Deep learning tutorials (2nd ed.)

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